code: def test_read_embedding_file_inside_archive(self):
      token2vec = {
          "think": torch.Tensor([0.143, 0.189, 0.555, 0.361, 0.472]),
          "make": torch.Tensor([0.878, 0.651, 0.044, 0.264, 0.872]),
          "difference": torch.Tensor(
              [0.053, 0.162, 0.671, 0.110, 0.259]
          ),
          "àèìòù": torch.Tensor([1.0, 2.0, 3.0, 4.0, 5.0]),
      }
      vocab = Vocabulary()
      for token in token2vec:
          vocab.add_token_to_namespace(token)
  
      params = Params(
          {
              "pretrained_file": str(
                  self.FIXTURES_ROOT
                  / "embeddings/multi-file-archive.zip"
              ),
              "embedding_dim": 5,
          }
      )
      with pytest.raises(
          ValueError,
          match="The archive .*/embeddings/multi-file-archive.zip contains multiple files, "
          "so you must select one of the files inside "
          "providing a uri of the type: "
          "\\(path_or_url_to_archive\\)#path_inside_archive\\.",
      ):
          Embedding.from_params(params, vocab=vocab)
  
      for ext in [".zip", ".tar.gz"]:
          archive_path = (
              str(self.FIXTURES_ROOT / "embeddings/multi-file-archive")
              + ext
          )
          file_uri = format_embeddings_file_uri(
              archive_path, "folder/fake_embeddings.5d.txt"
          )
          params = Params(
              {"pretrained_file": file_uri, "embedding_dim": 5}
          )
          embeddings = Embedding.from_params(
              params, vocab=vocab
          ).weight.data
          for tok, vec in token2vec.items():
              i = vocab.get_token_index(tok)
              assert torch.equal(embeddings[i], vec), (
                  "Problem with format " + archive_path
              )
  
imports: import gzip
  import warnings
  import numpy
  import pytest
  import torch
  from allennlp.common import Params
  from allennlp.common.checks import ConfigurationError
  from allennlp.common.testing import AllenNlpTestCase
  from allennlp.data import Vocabulary
  from allennlp.modules.token_embedders.embedding import _read_pretrained_embeddings_file, Embedding, EmbeddingsTextFile, format_embeddings_file_uri, parse_embeddings_file_uri
label_desc: Use image node_id 7 for calling the TestEmbedding obj's underlying member method code with example usage: obj.test_read_embedding_file_inside_archive() without return types